---
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlnet-base-cased-HU
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# xlnet-base-cased-HU

This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8571
- Accuracy: 0.8465
- F1: 0.7979
- Precision: 0.875
- Recall: 0.7333

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.7086        | 1.0   | 64   | 0.6695          | 0.5866   | 0.0    | 0.0       | 0.0    |
| 0.6423        | 2.0   | 128  | 0.6102          | 0.6929   | 0.6777 | 0.5985    | 0.7810 |
| 0.5089        | 3.0   | 192  | 0.5276          | 0.7756   | 0.7016 | 0.7791    | 0.6381 |
| 0.491         | 4.0   | 256  | 0.8212          | 0.7559   | 0.6310 | 0.8413    | 0.5048 |
| 0.3367        | 5.0   | 320  | 0.6119          | 0.8189   | 0.7982 | 0.7398    | 0.8667 |
| 0.2412        | 6.0   | 384  | 0.4921          | 0.8346   | 0.7742 | 0.8889    | 0.6857 |
| 0.154         | 7.0   | 448  | 0.8891          | 0.8268   | 0.7609 | 0.8861    | 0.6667 |
| 0.1075        | 8.0   | 512  | 0.9218          | 0.8504   | 0.8021 | 0.8851    | 0.7333 |
| 0.081         | 9.0   | 576  | 0.8782          | 0.8465   | 0.7958 | 0.8837    | 0.7238 |
| 0.0727        | 10.0  | 640  | 0.8571          | 0.8465   | 0.7979 | 0.875     | 0.7333 |


### Framework versions

- Transformers 4.43.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1